At the end of October, the Instructure team had the chance to spend a full day onsite with Belmont University in Nashville, TN for a Customer Discovery Session (CDS) focused on the future of course design and assessment. Belmont is an innovative institution that has deliberately evolved its digital learning approach over the past several years. As Geoff Price, Director of Digital Learning and Innovation, shared, their team has shifted from a tech-only LMS mindset to designing cohesive, human-centered course experiences that better support faculty and students.
Belmont invited Instructure to campus to do more than product demos. The goal was to share Belmont’s course-building and assessment realities, explore early prototypes, and co-design solutions that could genuinely reduce friction while improving learning outcomes. Instructional designers, technologists, and faculty partners participated throughout the day, offering candid feedback and helping us pressure-test what matters most.
What we covered
Belmont and Instructure collaborated through hands-on activities and prototype discussions organized around the following themes:
Versatile Learning Evaluation
Belmont’s teams expressed interest in evolving assessment from a simple measure of correctness to a richer view of understanding. We explored how AI could be used to support more robust learning evaluation by:
- Building assessments as learning journeys: Shifting from single checks to sequenced experiences that guide students through preparation, practice, and application.
- Making student thinking visible: Giving learners more ways to demonstrate how they reason, especially in math and physics curriculum, so instructors not only see answers, but the path taken to get to those answers.
- Emphasizing growth over snapshots: Designing assessment cycles that surface early understanding, support practice in authentic contexts, and then re-check progress to highlight improvement over time.
Content Creation and Management
The instructional design team walked us through their processes and guidelines for building consistent courses at scale. Today, instructors receive blank course shells each term and copy content forward. Belmont visualized how course creation (and maintenance) could be enhanced:
- AI as a structured starting point: The group was interested in faculty-centered workflows where educators provide objectives, standards, and policies upfront, and AI generates a draft course that faculty then refine. This would best allow instructors to set clear start and end points while AI helps fill in the middle.
- Alignment to institutional design frameworks: Belmont shared their course guidelines and policies and described how these shape the day-to-day work of instructional designers and educators. They stressed that AI-generated content should reflect these frameworks to ensure the most efficient experience, as every institution has slightly differentiated ways of building and supporting course material.
- Smarter course copy, reuse, and sharing: Belmont’s CDS group noted that today’s copy and share workflows sometimes feel disjointed, especially for newer instructors. Through our discussion, we noted space for small-but-mighty UI/UX improvements that surface a single, clear action for copying or sharing, reduce cognitive load with bulk tools, and use AI to proactively suggest where content should go based on course context.
Authentic Assessment
Across disciplines, Belmont emphasized that authentic assessment is about realistic performance in context, not only knowledge recall. In prototype exploration and faculty discussions, they highlighted opportunities for AI to help:
- Convert abstract prompts into real scenarios: Instead of “write about crisis communication,” prepare students to deliver communications inside a specific, realistic PR situation.
- Enable scalable simulations: Health Sciences teams described the need for students to practice procedures online before clinical placements. They see an opportunity for AI-supported role play, scenario progression, and feedback that mimics real-world complexity.
- Make chatbots more human and meaningful: In piloting chatbot role-play assignments, they’ve seen examples where students engage strongly with immediate feedback. They’re interested in richer experiences, more natural dialogue and visual/character context.
Our key takeaways
AI should accelerate course design, not replace the educator
While this certainly isn’t the first (or last) time we’ve heard this, it reemphasizes previous CDS discussions. Like many other institutions, Belmont is open to AI doing more of the heavy lift in course creation if it reduces startup time and helps instructors iterate faster. The key element is having the AI be intelligent and accept prompts that support their custom guidelines and expectations.
Course copy is a maintenance moment, not a clone
Copied courses often need cleanup: old announcements, broken pacing, duplicated items, embedded specific dates, and missing faculty presence. We have an opportunity to make course copy or content sharing feel like a guided refresh, with smart flags, review checkpoints, and prompts for key updates like welcome videos, bios, and syllabi.
The most valuable assessments show thinking
Learning is proven through reasoning. Belmont strives to create assessments that reveal how students process, apply, and transfer knowledge even if and when multiple choice is required for accreditation. There is excitement by AI’s potential to assist in generating alternate modalities and help educators build more meaningful item banks.
Looking Ahead
Belmont’s onsite visit was a powerful reminder that the best products come from co-designing with real institutions. Their teams didn’t just react to our ideas, they helped to shape them by grounding every discussion in what faculty and students need most: consistency, clarity, authentic learning, and less busywork.
We’re grateful to Belmont’s instructional designers, technologists, and faculty for their partnership and candor. The insights from this experience will directly inform how we refine these prototypes and continue building toward a more supportive, more authentic, and more human future for teaching and learning.
